@conference {18669,
	title = {Evaluating Files to Audit for Detecting Intrusions in FileSystem Data},
	year = {2009},
	month = {2009/07//},
	pages = {163 - 170},
	abstract = {Monitoring filesystem data is a common method used to detect intrusions. Once a computer is compromised, an attacker may alter files, add new files or delete existing files. The changes that attackers make may target any part of the filesystem, including metadata along with files (e.g., permissions, ownerships and inodes). The accuracy of detecting an intrusion depends on the data audited: if an intrusion does not manifest in the data, the intrusion will not be detected. Moreover, not all files, which contain filesystem activity, are suitable to detect intrusions, as some may fail to provide useful information. In this paper, we describe an empirical study that focused on filesystem attack activity after a SSH compromise. Three types of attacker action are considered: reconnaissance, password modification, and malware download. For each type of action, we evaluated the files to audit using metrics derived from the field of information theory and estimated with the empirical SSH compromise data.},
	keywords = {authorisation, Bayes methods, Bayesian metric, data auditing, empirical SSH compromise data, Entropy, entropy-based metric, file evaluation, file organisation, filesystem attack activity, filesystem data monitoring, honeypot, information theory, intrusion detection system, invasive software, malware download, meta data, optimisation, optimization problem, password modification, probability, reconnaissance action, unauthorized user},
	doi = {10.1109/NCA.2009.38},
	author = {Molina,J. and Michel Cukier}
}
@conference {18654,
	title = {An empirical study of filesystem activity following a SSH compromise},
	year = {2007},
	month = {2007/12//},
	pages = {1 - 5},
	abstract = {Monitoring filesystem data is a common method used to detect attacks. Once a computer is compromised, attackers will likely alter files, add new files or delete existing files. The changes that attackers make may target any part of the filesystem, including metadata along with files (e.g., permissions, ownerships and inodes). In this paper, we describe an empirical study that focused on SSH compromised attacks. First statistical data on the number of files targeted and the associated activity (e.g., read, write, delete, ownership and rights) is reported. Then, we refine the analysis to identify and understand patterns in the attack activity.},
	keywords = {attack activity, filesystem activity, filesystem data monitoring, intrusion detection systems evaluation, meta data, metadata, security of data, SSH compromised attacks},
	doi = {10.1109/ICICS.2007.4449675},
	author = {Molina,J. and Gordon,J. and Chorin,X. and Michel Cukier}
}
@conference {13849,
	title = {Reranking for Sentence Boundary Detection in Conversational Speech},
	booktitle = {2006 IEEE International Conference on Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings},
	volume = {1},
	year = {2006},
	month = {2006/05/14/19},
	pages = {I-I - I-I},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We present a reranking approach to sentence-like unit (SU) boundary detection, one of the EARS metadata extraction tasks. Techniques for generating relatively small n-best lists with high oracle accuracy are presented. For each candidate, features are derived from a range of information sources, including the output of a number of parsers. Our approach yields significant improvements over the best performing system from the NIST RT-04F community evaluation},
	keywords = {Automatic speech recognition, conversational speech, data mining, Ear, EARS metadata extraction tasks, Feature extraction, hidden Markov models, meta data, Model driven engineering, NIST, NIST RT-04F community evaluation, oracle accuracy, performance evaluation, reranking, sentence-like unit boundary detection, Speech processing, Speech recognition, Telephony},
	isbn = {1-4244-0469-X},
	doi = {10.1109/ICASSP.2006.1660078},
	author = {Roark,B. and Liu,Yang and Harper,M. and Stewart,R. and Lease,M. and Snover,M. and Shafran,I. and Dorr, Bonnie J and Hale,J. and Krasnyanskaya,A. and Yung,L.}
}
@conference {17878,
	title = {Improving access to multi-dimensional self-describing scientific datasets},
	booktitle = {3rd IEEE/ACM International Symposium on Cluster Computing and the Grid, 2003. Proceedings. CCGrid 2003},
	year = {2003},
	month = {2003/05/12/15},
	pages = {172 - 179},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Applications that query into very large multidimensional datasets are becoming more common. Many self-describing scientific data file formats have also emerged, which have structural metadata to help navigate the multi-dimensional arrays that are stored in the files. The files may also contain application-specific semantic metadata. In this paper, we discuss efficient methods for performing searches for subsets of multi-dimensional data objects, using semantic information to build multidimensional indexes, and group data items into properly sized chunks to maximize disk I/O bandwidth. This work is the first step in the design and implementation of a generic indexing library that will work with various high-dimension scientific data file formats containing semantic information about the stored data. To validate the approach, we have implemented indexing structures for NASA remote sensing data stored in the HDF format with a specific schema (HDF-EOS), and show the performance improvements that are gained from indexing the datasets, compared to using the existing HDF library for accessing the data.},
	keywords = {Application software, application-specific semantic metadata, Bandwidth, Computer science, database indexing, disk I/O bandwidth, distributed databases, Educational institutions, Indexing, indexing structures, Libraries, meta data, Middleware, multidimensional arrays, multidimensional datasets, Multidimensional systems, NASA, NASA remote sensing data, Navigation, query formulation, self-describing scientific data file formats, structural metadata, very large databases},
	isbn = {0-7695-1919-9},
	doi = {10.1109/CCGRID.2003.1199366},
	author = {Nam,B. and Sussman, Alan}
}
@conference {16779,
	title = {Integrating distributed scientific data sources with MOCHA and XRoaster},
	booktitle = {Thirteenth International Conference on Scientific and Statistical Database Management, 2001. SSDBM 2001. Proceedings},
	year = {2001},
	month = {2001///},
	pages = {263 - 266},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {MOCHA is a novel middleware system for integrating distributed data sources that we have developed at the University of Maryland. MOCHA is based on the idea that the code that implements user-defined types and functions should be automatically deployed to remote sites by the middleware system itself. To this end, we have developed an XML-based framework to specify metadata about data sites, data sets, and user-defined types and functions. XRoaster is a graphical tool that we have developed to help the user create all the XML metadata elements to be used in MOCHA},
	keywords = {client-server systems, data sets, data sites, Databases, Distributed computing, distributed databases, distributed scientific data source integration, Educational institutions, graphical tool, hypermedia markup languages, IP networks, java, Large-scale systems, Maintenance engineering, meta data, metadata, Middleware, middleware system, MOCHA, Query processing, remote sites, scientific information systems, user-defined types, visual programming, XML, XML metadata elements, XML-based framework, XRoaster},
	isbn = {0-7695-1218-6},
	doi = {10.1109/SSDM.2001.938560},
	author = {Rodriguez-Martinez,M. and Roussopoulos, Nick and McGann,J. M and Kelley,S. and Mokwa,J. and White,B. and Jala,J.}
}
@conference {16466,
	title = {Optimized seamless integration of biomolecular data},
	booktitle = {Proceedings of the IEEE 2nd International Symposium on Bioinformatics and Bioengineering Conference, 2001},
	year = {2001},
	month = {2001/11/04/6},
	pages = {23 - 32},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Today, scientific data is inevitably digitized, stored in a variety of heterogeneous formats, and is accessible over the Internet. Scientists need to access an integrated view of multiple remote or local heterogeneous data sources. They then integrate the results of complex queries and apply further analysis and visualization to support the task of scientific discovery. Building a digital library for scientific discovery requires accessing and manipulating data extracted from flat files or databases, documents retrieved from the Web, as well as data that is locally materialized in warehouses or is generated by software. We consider several tasks to provide optimized and seamless integration of biomolecular data. Challenges to be addressed include capturing and representing source capabilities; developing a methodology to acquire and represent metadata about source contents and access costs; and decision support to select sources and capabilities using cost based and semantic knowledge, and generating low cost query evaluation plans},
	keywords = {analysis, Bioinformatics, biology computing, cost based knowledge, Costs, Data analysis, data mining, data visualisation, Data visualization, Data warehouses, decision support, digital library, Educational institutions, information resources, Internet, low cost query evaluation plans, Mediation, meta data, metadata, molecular biophysics, multiple local heterogeneous data sources, multiple remote heterogeneous data sources, optimized seamless biomolecular data integration, scientific discovery, scientific information systems, semantic knowledge, software libraries, visual databases, Visualization},
	isbn = {0-7695-1423-5},
	doi = {10.1109/BIBE.2001.974408},
	author = {Eckman,B. A and Lacroix,Z. and Raschid, Louiqa}
}
